Results 201 to 210 of about 98,080 (242)
Some of the next articles are maybe not open access.
2019
This lesson centers around the marginal value theorem (MVT, Charnov 1976), which describes how animals should forage in patches. It serves as a pre-lab to teach MVT basics, vectors, ANOVA, and basic plotting.
McWhirt, Mary, Weigel, Emily
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This lesson centers around the marginal value theorem (MVT, Charnov 1976), which describes how animals should forage in patches. It serves as a pre-lab to teach MVT basics, vectors, ANOVA, and basic plotting.
McWhirt, Mary, Weigel, Emily
openaire +1 more source
Parallel Bacterial Foraging Optimization
2011This chapter focuses on concept of new variant of Bacterial Foraging Optimization (BFO) named as Parallel Bacterial Foraging Optimization (PBFO). The key issues on implementation of PBFO in parallel architecture are also addressed. PBFO and its fusions with Particle Swarm Optimization (PSO) and its variants to optimize multimodal functions with high ...
S. S. Pattnaik +4 more
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Honeyeater foraging: A test of optimal foraging theory
Animal Behaviour, 1981Abstract Honeyeaters (Meliphagidae) were observed foraging for nectar from Lambertia formosa inflorescences, each of which has seven flowers. The frequency distribution of numbers of flowers probed per visit to an inflorescence was found to be bimodal, with one peak at two and the other at seven.
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Selecting the optimal immunotherapy regimen in driver-negative metastatic NSCLC
Nature Reviews Clinical Oncology, 2021Roy S Herbst, Sarah B Goldberg
exaly
Bumblebee Foraging Optimization Algorithm
Heuristic optimization algorithms are important tools for solving complex optimization problems, particularly those involving high-dimensional, nonlinear, and multi-extremal functions. This paper proposes a heuristic optimization algorithm based on the foraging behavior of bumblebees, named Bumblebee Foraging Optimization (BFO).openaire +1 more source

